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Bayesian Statistics: The three cultures

(statmodeling.stat.columbia.edu)
309 points luu | 1 comments | 26 Jul 24 17:15 UTC | HN request time: 0s | source
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thegginthesky ◴[26 Jul 24 17:55 UTC] No.41080693[source]▶
I miss the college days where professors would argue endlessly on Bayesian vs Frequentist.

The article is very well succinct and even explains why even my Bayesian professors had different approaches to research and analysis. I never knew about the third camp, Pragmatic Bayes, but definitely is in line with a professor's research that was very through on probability fit and the many iteration to get the prior and joint PDF just right.

Andrew Gelman has a very cool talk "Andrew Gelman - Bayes, statistics, and reproducibility (Rutgers, Foundations of Probability)", which I highly recommend for many Data Scientists

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spootze ◴[26 Jul 24 18:11 UTC] No.41080841[source]▶
Regarding the frequentist vs bayesian debates, my slightly provocative take on these three cultures is

- subjective Bayes is the strawman that frequentist academics like to attack

- objective Bayes is a naive self-image that many Bayesian academics tend to possess

- pragmatic Bayes is the approach taken by practitioners that actually apply statistics to something (or in Gelman’s terms, do science)

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refulgentis ◴[26 Jul 24 18:37 UTC] No.41081070[source]▶
I see, so academics are frequentists (attackers) or objective Bayes (naive), and the people Doing Science are pragmatic (correct).

The article gave me the same vibe, nice, short set of labels for me to apply as a heuristic.

I never really understood this particular war, I'm a simpleton, A in Stats 101, that's it. I guess I need to bone up on Wikipedia to understand what's going on here more.

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1. runarberg ◴[26 Jul 24 19:13 UTC] No.41081388[source]▶
I understand the war between bayesians and frequentists. Frequentist methods have been misused for over a century now to justify all sorts of pseudoscience and hoaxes (as well as created a fair share of honest mistakes), so it is understandable that people would come forward and claim there must be a better way.

What I don’t understand is the war between naive bayes and pragmatic bayes. If it is real, it seems like the extension of philosophers vs. engineers. Scientists should see value in both. Naive Bayes is important to the philosophy of science, without which there would be a lot of junk science which would go unscrutinized for far to long, and engineers should be able to see the value of philosophers saving them works by debunking wrong science before they start to implement theories which simply will not work in practice.